





'''simple docstring'''






import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 		lowerCamelCase	(   _A   , unittest.TestCase							):
	snake_case_   = CLIPTokenizer
	snake_case_   = CLIPTokenizerFast
	snake_case_   = True
	snake_case_   = {}
	snake_case_   = False



	def 	_lowerCamelCase     ( self						):
			super().setUp()

			# fmt: off
			lowerCAmelCase  :     str       						= ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
			# fmt: on
			lowerCAmelCase  :     str       						= dict(zip(a_		,   range(len(a_						)						)						)						)
			lowerCAmelCase  :     Tuple       						= ["#version: 0.2", "l o", "lo w</w>", "e r</w>"]
			lowerCAmelCase  :     Tuple       						= {"unk_token": "<unk>"}

			lowerCAmelCase  :     Any       						= os.path.join(self.tmpdirname		,   VOCAB_FILES_NAMES["vocab_file"]						)
			lowerCAmelCase  :     int       						= os.path.join(self.tmpdirname		,   VOCAB_FILES_NAMES["merges_file"]						)
			with open(self.vocab_file		,   "w"		,   encoding="utf-8"						) as fp:
					fp.write(json.dumps(a_						) + "\n"						)
			with open(self.merges_file		,   "w"		,   encoding="utf-8"						) as fp:
					fp.write("\n".join(a_						)						)



	def 	_lowerCamelCase     ( self		,   **a_						):
			kwargs.update(self.special_tokens_map						)
			return CLIPTokenizer.from_pretrained(self.tmpdirname		,   **a_						)



	def 	_lowerCamelCase     ( self		,   **a_						):
			kwargs.update(self.special_tokens_map						)
			return CLIPTokenizerFast.from_pretrained(self.tmpdirname		,   **a_						)



	def 	_lowerCamelCase     ( self		,   a_						):
			lowerCAmelCase  :     int       						= "lower newer"
			lowerCAmelCase  :     Optional[Any]       						= "lower newer"
			return input_text, output_text



	def 	_lowerCamelCase     ( self						):
			lowerCAmelCase  :     Optional[int]       						= CLIPTokenizer(self.vocab_file		,   self.merges_file		,   **self.special_tokens_map						)
			lowerCAmelCase  :     int       						= "lower newer"
			lowerCAmelCase  :     Optional[int]       						= ["lo", "w", "er</w>", "n", "e", "w", "er</w>"]
			lowerCAmelCase  :     Union[str, Any]       						= tokenizer.tokenize(a_						)
			self.assertListEqual(a_		,   a_						)

			lowerCAmelCase  :     Optional[int]       						= tokens + [tokenizer.unk_token]
			lowerCAmelCase  :     Optional[Any]       						= [10, 2, 16, 9, 3, 2, 16, 20]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(a_						)		,   a_						)



	@require_ftfy
	def 	_lowerCamelCase     ( self						):
			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
					with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
							lowerCAmelCase  :     List[Any]       						= self.tokenizer_class.from_pretrained(a_		,   **a_						)
							lowerCAmelCase  :     str       						= self.rust_tokenizer_class.from_pretrained(a_		,   **a_						)

							lowerCAmelCase  :     Union[str, Any]       						= "A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."
							lowerCAmelCase  :     int       						= tokenizer_s.tokenize(a_						)
							lowerCAmelCase  :     str       						= tokenizer_r.tokenize(a_						)

							self.assertListEqual(a_		,   a_						)

							# Test that the tokenization is identical on an example containing a character (Latin Small Letter A
							# with Tilde) encoded in 2 different ways
							lowerCAmelCase  :     Any       						= "xa\u0303y" + " " + "x\xe3y"
							lowerCAmelCase  :     Dict       						= tokenizer_s.tokenize(a_						)
							lowerCAmelCase  :     Union[str, Any]       						= tokenizer_r.tokenize(a_						)

							self.assertListEqual(a_		,   a_						)

							# Test that the tokenization is identical on unicode of space type
							lowerCAmelCase  :     Optional[Any]       						= [
							    "\u0009",  # (horizontal tab, '\t')
							    "\u000B",  # (vertical tab)
							    "\u000C",  # (form feed)
							    "\u0020",  # (space, ' ')
							    "\u200E",  # (left-to-right mark):w
							    "\u200F",  # (right-to-left mark)
							]
							for unicode_seq in spaces_unicodes:
									lowerCAmelCase  :     Tuple       						= tokenizer_s.tokenize(a_						)
									lowerCAmelCase  :     Optional[Any]       						= tokenizer_r.tokenize(a_						)

									self.assertListEqual(a_		,   a_						)

							# Test that the tokenization is identical on unicode of line break type
							lowerCAmelCase  :     Union[str, Any]       						= [
							    "\u000A",  # (line feed, '\n')
							    "\r\n",  # (carriage return and line feed, '\r\n')
							    "\u000D",  # (carriage return, '\r')
							    "\r",  # (carriage return, '\r')
							    "\u000D",  # (carriage return, '\r')
							    "\u2028",  # (line separator)
							    "\u2029",  # (paragraph separator)
							    # "\u0085", # (next line)
							]

							# The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
							# it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
							# space (and thus into an empty list).

							for unicode_seq in line_break_unicodes:
									lowerCAmelCase  :     Any       						= tokenizer_s.tokenize(a_						)
									lowerCAmelCase  :     str       						= tokenizer_r.tokenize(a_						)

									self.assertListEqual(a_		,   a_						)



	def 	_lowerCamelCase     ( self						):
			# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
					with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
							lowerCAmelCase  :     List[Any]       						= "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
							lowerCAmelCase  :     Union[str, Any]       						= F'''{text_of_1_token} {text_of_1_token}'''

							lowerCAmelCase  :     int       						= self.rust_tokenizer_class.from_pretrained(
							    a_		,   use_fast=a_		,   )
							lowerCAmelCase  :     Tuple       						= tokenizer_r(a_		,   return_offsets_mapping=a_		,   add_special_tokens=a_						)
							self.assertEqual(encoding.offset_mapping[0]		,   (0, len(a_						))						)
							self.assertEqual(
							    encoding.offset_mapping[1]		,   (len(a_						) + 1, len(a_						) + 1 + len(a_						))		,   )

							lowerCAmelCase  :     Dict       						= F''' {text}'''

							lowerCAmelCase  :     Union[str, Any]       						= self.rust_tokenizer_class.from_pretrained(
							    a_		,   use_fast=a_		,   )
							lowerCAmelCase  :     List[str]       						= tokenizer_r(a_		,   return_offsets_mapping=a_		,   add_special_tokens=a_						)
							self.assertEqual(encoding.offset_mapping[0]		,   (1, 1 + len(a_						))						)
							self.assertEqual(
							    encoding.offset_mapping[1]		,   (1 + len(a_						) + 1, 1 + len(a_						) + 1 + len(a_						))		,   )



	def 	_lowerCamelCase     ( self						):
			# Test related to the breaking change introduced in transformers v4.17.0
			# We need to check that an error in raised when the user try to load a previous version of the tokenizer.
			with self.assertRaises(a_						) as context:
					self.rust_tokenizer_class.from_pretrained("robot-test/old-clip-tokenizer"						)

			self.assertTrue(
			    context.exception.args[0].startswith(
			        "The `backend_tokenizer` provided does not match the expected format."						)						)



	@require_ftfy
	def 	_lowerCamelCase     ( self						):
			super().test_tokenization_python_rust_equals()





	def 	_lowerCamelCase     ( self						):
			# CLIP always lower cases letters
			pass










'''simple docstring'''






def   __A    (				a_    :	list[list[float]]						):
		lowerCAmelCase  :     list[list[float]]       						= []
		for data in source_data:
				for i, el in enumerate(a_						):
						if len(a_						) < i + 1:
								data_lists.append([]						)
						data_lists[i].append(float(a_						)						)
		return data_lists






def   __A    (				a_    :	list[list[float]]   ,a_    :	list[int]						):
		lowerCAmelCase  :     list[list[float]]       						= []
		for dlist, weight in zip(a_   ,a_						):
				lowerCAmelCase  :     Optional[Any]       						= min(a_						)
				lowerCAmelCase  :     List[str]       						= max(a_						)

				lowerCAmelCase  :     list[float]       						= []
				# for weight 0 score is 1 - actual score
				if weight == 0:
						for item in dlist:
								try:
										score.append(1 - ((item - mind) / (maxd - mind))						)
								except ZeroDivisionError:
										score.append(1						)

				elif weight == 1:
						for item in dlist:
								try:
										score.append((item - mind) / (maxd - mind)						)
								except ZeroDivisionError:
										score.append(0						)

        # weight not 0 or 1
				else:
						lowerCAmelCase  :     List[Any]       						= f'''Invalid weight of {weight:f} provided'''
						raise ValueError(a_						)

				score_lists.append(a_						)

		return score_lists






def   __A    (				a_    :	list[list[float]]						):
		lowerCAmelCase  :     list[float]       						= [0 for i in range(len(score_lists[0]						)						)]

		for slist in score_lists:
				for j, ele in enumerate(a_						):
						lowerCAmelCase  :     Optional[Any]       						= final_scores[j] + ele

		return final_scores






def   __A    (				a_    :	list[list[float]]   ,a_    :	list[int]						):
		lowerCAmelCase  :     Union[str, Any]       						= get_data(a_						)
		lowerCAmelCase  :     List[Any]       						= calculate_each_score(a_   ,a_						)
		lowerCAmelCase  :     Optional[Any]       						= generate_final_scores(a_						)

		# append scores to source data
		for i, ele in enumerate(a_						):
				source_data[i].append(a_						)

		return source_data



